Optimal design method for offshore wind farm layout considering booster stations

Abstract

The present invention relates to an offshore wind farm layout optimization design method that takes into account a booster station, applicable to the field of wind power planning and design. The method comprises: generating a two-dimensional grid covering the planned site, the two-dimensional grid being formed by the intersection of multiple mutually parallel first straight lines and multiple mutually parallel second straight lines; using a genetic algorithm to determine the optimal parameters of the two-dimensional grid with the goal of maximizing the annual power generation of the planned site; determining the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determining a wind turbine row based on a first straight line on the two-dimensional grid, placing two wind turbines at both ends of the wind turbine row at the intersections of the corresponding first straight lines and the boundary of the planned site, and using the spacing between adjacent wind turbines in the wind turbine row as a first variable, using a genetic algorithm to determine the optimal first variable with the goal of maximizing the annual power generation of the planned site. The present invention is used to fully utilize the sea area of ​​the planned site and obtain a design solution that maximizes power generation.

Description

Technical Field

[0001] The present invention relates to the field of wind power planning and design, and in particular to an offshore wind farm layout optimization design method considering booster stations. Background Art

[0002] To ensure safe navigation at sea, wind power projects often require wind turbines to be arranged in a regular matrix. In coastal provinces like Zhejiang, which are rich in fishery resources, the layout of booster stations has been further standardized based on marine functional zoning and fishery production needs. These stations, used for voltage boosting and power collection, must be arranged in the same row as wind turbines.

[0003] To address this engineering constraint, the conventional engineering approach during microsite design for offshore wind farms is to add a booster station location based on the number of wind turbines required to meet the planned capacity. Planning engineers will first develop several layout plans based on experience that meet the required layout requirements. Using commercial software such as WAsP, they will select the layout plan with the highest power generation capacity and submit it to the electrical engineer. The electrical engineer will then determine the specific location for the booster station based on the recommended layout plan. In some cases, the electrical engineer will directly select a location from the layout plan as the booster station location.

[0004] It is obvious that the traditional method based on manual comparison has major shortcomings: 1. The number of comparison options is limited, and each option relies on the personal experience of engineers, which largely determines the pros and cons of the final recommended layout option; 2. The staged method of determining the location of the substation is obviously not scientific enough. Specifically, although the planning engineer gave a recommended layout option based on the maximum power generation as the judgment criterion in the first stage, after the electrical engineer replaced the wind turbine in the layout option with the substation, the wake effect between the wind turbines around the substation changed, resulting in the original plan with the highest power generation being likely not the highest power generation compared to the other alternative plans (which also replaced the wind turbine with the substation).

[0005] In addition, in the wind farm layout plan obtained based on traditional layout strategies, the wind turbines at both ends of each wind turbine row are mostly located within the planned site, failing to fully utilize the sea area of ​​the planned site, thus limiting its engineering practicality. Summary of the Invention

[0006] The technical problem to be solved by the present invention is: in response to the above-mentioned problems, a method for optimizing the layout of offshore wind farms taking into account booster stations is provided.

[0007] The technical solution adopted by the present invention is: a method for optimizing the layout of offshore wind farms considering booster stations, comprising:

[0008] Obtain the boundary information of the planned site, the number and model parameters of the wind turbines to be installed in the site, and a representative annual wind resource dataset at the hub height of the wind turbines;

[0009] generating a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines;

[0010] The genetic algorithm is used to determine the optimal parameters of the two-dimensional grid, with the parameters of the two-dimensional grid as variables, the grid points of the two-dimensional grid in the planning area as the locations where wind turbines and booster stations are to be installed, and the goal is to maximize the annual power generation of the planning area.

[0011] Based on the optimal parameters of the two-dimensional grid, the two-dimensional grid is determined, and the wind turbine row is determined based on the first straight line on the two-dimensional grid. The two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site. The spacing between adjacent wind turbines in the wind turbine row is used as the first variable. With the goal of maximizing the annual power generation of the planned site, a genetic algorithm is used to determine the optimal first variable.

[0012] include:

[0013] When the number of wind turbines on the wind turbine row is 1, the distance between the wind turbine point and the intersection of the first straight line and the planned site boundary is set as the second variable;

[0014] When the number of wind turbines on the wind turbine row is 2, place the two wind turbines at the two intersections of the corresponding first straight line and the boundary of the planned site;

[0015] When the number of wind turbines in a wind turbine row is greater than 2, the two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site, and the spacing between adjacent wind turbines in the wind turbine row is used as the first variable;

[0016] Taking the first and second variables as optimization variables and maximizing the annual power generation of the planned site as the goal, a genetic algorithm is used to determine the optimal first and second variables.

[0017] The grid points of the two-dimensional grid within the planned site are used as the locations for installing wind turbines and booster stations, including:

[0018] Based on the geometric center of gravity of the planned site and the positional relationship between the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned site;

[0019] Calculate the distance from each grid point of the two-dimensional grid within the planning area to the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station.

[0020] The calculation of the annual power generation of the planned site includes:

[0021] Determine whether the number of grid points in the two-dimensional grid within the planning area is equal to ,in The number of wind turbines to be installed in the planned area;

[0022] If the number of grid points in the planning area is not equal to , the preset minimum value is used as the annual power generation of the planned site; otherwise, it is determined whether the distance between adjacent grid points is greater than the preset minimum distance;

[0023] If the spacing between adjacent grid points is less than the preset minimum spacing, the preset minimum value is used as the annual power generation of the planned site; otherwise, the annual power generation of the planned site is calculated based on the location of each wind turbine in the planned site, combined with the model parameters and the representative annual wind resource data set.

[0024] The calculation of the annual power generation of the planned area based on the location of each wind turbine in the planned area, combined with the model parameters and the representative annual wind resource data set, includes:

[0025] Assume that the boost station is located at a virtual wind turbine, the output power of the virtual wind turbine is always 0, and the thrust coefficient is set to 0.001;

[0026] Divide the basic wind conditions based on wind speed and wind direction, and combine with the representative annual wind resource dataset to determine the basic wind conditions corresponding to each period of the representative year, as well as the proportion of each basic wind condition in the representative year and the representative wind speed and representative wind direction of each basic wind condition;

[0027] Based on the representative wind speed and representative wind direction of each basic wind condition and the location of each wind turbine in the planned area, calculate the wind speed loss of each wind turbine in the area affected by the wake of the upwind wind turbine under each basic wind condition;

[0028] Determine the effective wind speed of each wind turbine under each basic wind condition based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine;

[0029] Based on the effective wind speed of each wind turbine under each basic wind condition, the power generation of each wind turbine under each basic wind condition is determined, and then the power generation under each basic wind condition is determined;

[0030] Based on the power generation under each basic wind condition and the proportion of each basic wind condition in the representative year, the annual power generation of the planned site in the representative year is determined.

[0031] The basic wind conditions based on wind speed and wind direction include:

[0032] The cut-in wind speed of the wind turbine model to be installed in the planning area and cut-out wind speed As the maximum value and the minimum value, multiple wind speed intervals are divided between the maximum value and the minimum value;

[0033] Evenly divide the wind direction angle from 0-360° into multiple wind direction sectors;

[0034] The wind speed ranges and wind direction sectors are combined in pairs to form multiple basic wind conditions.

[0035] An offshore wind farm layout optimization design device considering a booster station comprises:

[0036] The information acquisition module is used to obtain the boundary information of the planned site, the number and model parameters of the wind turbines to be installed in the site, and the representative annual wind resource dataset at the hub height of the wind turbines;

[0037] A grid generation module, configured to generate a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines;

[0038] The parameter optimization module is used to determine the optimal parameters of the two-dimensional grid using genetic algorithms, with the parameters of the two-dimensional grid as variables and the grid points of the two-dimensional grid within the planning area as the locations for installing wind turbines and booster stations, with the goal of maximizing the annual power generation of the planning area;

[0039] The point determination module is used to determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determine the wind turbine row based on the first straight line on the two-dimensional grid, place the two wind turbines at the two intersections of the corresponding first straight line and the boundary of the planned site, and use the spacing between adjacent wind turbines in the wind turbine row as the first variable. With the goal of maximizing the annual power generation of the planned site, a genetic algorithm is used to determine the optimal first variable.

[0040] A storage medium stores a computer program that can be executed by a processor, and when the computer program is executed, the steps of the offshore wind farm layout optimization design method considering booster stations are implemented.

[0041] An offshore wind farm layout optimization design device comprises a memory and a processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering booster stations are implemented.

[0042] The beneficial effects of the present invention are as follows: the present invention optimizes the layout of the wind farm by covering the two-dimensional grid of the planned site, using the parameters of the two-dimensional grid as variables, and the grid points as the locations of wind turbines and booster stations. It can obtain a design scheme that meets the requirements of the regular arrangement of rows and columns of wind turbines and booster stations and maximizes the power generation according to the geometric boundaries of the planned site, the information of the models to be assembled in the site, and the distribution of wind energy resources through iterative optimization using a genetic algorithm.

[0043] In the optimization calculation, the present invention faces the engineering constraint that the booster station needs to be arranged in the same row as the wind turbines. According to the principle of the shortest line between the booster station and each wind turbine, or according to the geometric center of gravity of the planned site and the intersection of the outgoing submarine cable line and the outer boundary of the planned site, and following the principle of minimum distance priority, a dynamic booster station location determination method is proposed, thereby realizing the integrated optimization of the booster station and wind turbine layout design.

[0044] The present invention determines the preliminary locations of the booster station and each wind turbine through a two-dimensional grid, places the two wind turbines at the two intersections of the corresponding first straight line and the boundary of the planned site, takes the spacing between adjacent wind turbines in the wind turbine row as a variable, and uses a genetic algorithm to re-optimize the spacing between adjacent wind turbines in each row, thereby achieving full utilization of the sea area of ​​the planned site.

[0045] The present invention overcomes the problems of traditional manual selection methods that are highly dependent on engineer experience, have a limited number of selection options, and determine the locations of booster stations in stages, making it difficult to accurately obtain high-quality solutions for projects with large power generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart for optimizing the layout of offshore wind farms considering booster stations in an embodiment.

[0047] Figure 2 Schematic diagram of the planning site under different coordinate systems.

[0048] Figure 3 Schematic diagram of machine layout optimization based on two-dimensional grid.

[0049] Figure 4 Flowchart for the calculation of two-dimensional grid parameter optimization.

[0050] Figure 5 Schematic diagram of the method for determining the relative position relationship between grid points and polygonal planning areas.

[0051] Figure 6 This is a schematic diagram of the booster station location under the specified layout plan.

[0052] Figure 7 The flowchart for calculating the annual power generation of an offshore wind farm considering a booster station under a specified layout scheme.

[0053] Figure 8 Schematic diagram for re-optimization of wind turbine locations. DETAILED DESCRIPTION

[0054] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention and are not to be construed as limiting the present invention. The step numbers in the following embodiments are provided for ease of explanation only and do not limit the order of the steps. The order of execution of the steps in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0055] In the description of the present invention, "a plurality" means two or more. The terms "first" and "second" are used solely to distinguish technical features and are not to be construed as indicating or implying relative importance, or as implicitly indicating the number of the indicated technical features, or as implicitly indicating the order of the indicated technical features. Furthermore, unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art.

[0056] Example 1: Figure 1 As shown, this embodiment is a method for optimizing the layout of offshore wind farms considering booster stations, specifically including:

[0057] S100: Obtain boundary information of the planned site and the number of wind turbines to be installed in the site and model parameters, as well as a representative annual wind resource dataset at the hub height of the wind turbine.

[0058] Take any point as the coordinate origin, with due east as the positive x-axis and due north as the positive y-axis, to establish a rectangular coordinate system, also known as a geodetic coordinate system. Based on the acquired boundary information for the planned site, determine the horizontal and vertical coordinates of each boundary point in the geodetic coordinate system. If the planned site includes a restricted area where wind turbines cannot be deployed, the horizontal and vertical coordinates of each boundary point that encloses the restricted area must also be determined.

[0059] The shape of the planned site and its restricted area is as follows: Figure 2 As shown, the coordinates of each outer boundary point in the geodetic coordinate system can be expressed as , the coordinates of each boundary point in the restricted area can be expressed as .

[0060] In this embodiment, the model parameters include the hub height H, the rotor diameter D, and a wind speed-aerodynamic parameter list. The wind speed-aerodynamic parameter list can be obtained from the whole machine manufacturer, covering the thrust coefficient and power at various typical wind speeds within the effective wind speed range (cut-in wind speed to cut-out wind speed) for normal operation and power generation of the corresponding model wind turbine.

[0061] In this example, the representative annual wind resource dataset at the hub height of the wind turbine refers to a set of representative wind resource data obtained after processing the measured wind data, which can reflect the long-term average level of the wind farm. It includes wind speed and direction in 8760 time periods with each period being 1 hour.

[0062] According to the coordinates of each boundary point on the outer boundary of the planned site, determine the coordinate value of the geometric center of gravity of the planned site in the geodetic coordinate system. The process is as follows:

[0063] 1. Calculate the area of ​​the planned site:

[0064] ;

[0065] 2. Determine the geometric center of gravity of the planned area:

[0066] ;

[0067] ;

[0068] Where, and Refers to the horizontal and vertical coordinates of the geometric center of gravity of the planning area respectively. Figure 2 The planning site polygon shown in , n=5, Take separately , Take separately .

[0069] To facilitate subsequent processing, the coordinate origin of the geodetic coordinate system is adjusted to the geometric center of gravity of the planning area obtained above, thereby obtaining the reference coordinate system ,like Figure 2 As shown. Further, determine the coordinates of each boundary point of the planning area in the reference coordinate system. Figure 2 For example, the boundary point A in the calculation formula is:

[0070] ;

[0071] ;

[0072] Where, and They represent the horizontal and vertical coordinates of the boundary point A in the reference coordinate system respectively.

[0073] S200, generating a two-dimensional grid covering the planned area ( Figure 3 ), the two-dimensional grid is composed of The first parallel straight lines and The second straight lines parallel to each other intersect to form.

[0074] In this embodiment, the distance between adjacent first straight lines is ; The distance between adjacent second straight lines is The angle between the first straight line and the preset first direction (in this case, the positive direction of the reference coordinate system X axis) is ; The angle between the second straight line and the first straight line is , by adjusting the parameters of the two-dimensional grid The value of can generate two-dimensional grids of different forms.

[0075] To ensure that the constructed two-dimensional grid can completely cover the planned area, it is recommended to take and is a large odd number, such as 1001. The middle straight line of the first straight line and The coordinates of the intersection point of the middle line of the second straight line ( , ) and They represent the minimum values ​​of the horizontal and vertical coordinates of the outer boundary points of the planning area in the reference coordinate system. This design not only ensures that the constructed two-dimensional grid completely covers the planning area, but also ensures the flexibility of the grid nodes located within the planning area.

[0076] S300, using the parameters of the two-dimensional grid as variables, the grid points of the two-dimensional grid in the planned area as the locations where wind turbines and booster stations are to be installed, and maximizing the annual power generation of the planned area as the goal, using a genetic algorithm to determine the optimal parameters of the two-dimensional grid.

[0077] S310, set the parameters of the two-dimensional grid Using the maximization of the planned site's annual power generation as the objective function, a genetic algorithm-based optimization model for plant layout was constructed. Based on the set population size Q, an initial population was randomly generated, where each individual represented a parameter solution for a two-dimensional grid.

[0078] In this embodiment, the grid points of the two-dimensional grid in the planning area are used as the points where the wind turbine and the booster station are to be installed. For example, the wind turbine coordinates are determined by the intersection of the i-th first straight line and the j-th second straight line. :

[0079] ;

[0080] ;

[0081] in, ;

[0082] S320, such as Figure 4 As shown in Figure 2, for the two-dimensional grid parameter scheme corresponding to any individual in the population, the constraint conditions must be checked before the annual power generation is calculated.

[0083] S321, determine whether the number of grid points in the two-dimensional grid in the planning area under the parameter scheme corresponding to the target individual is equal to ,in In order to plan the number of wind turbines to be installed in the site, 1 corresponds to the location for the construction of the substation.

[0084] In this embodiment, the "ray intersection method" is used to determine the relative position of each grid node and the planning area polygon. The core concept is: with the target grid node as the endpoint, a horizontal ray is drawn to the right (parallel to the X-axis of the reference coordinate system) and the number of intersections between the ray and the planning area polygon is calculated. If the number of intersections is odd, the grid node is determined to be inside the planning area polygon, while if it is even, the grid node is outside the planning area.

[0085] Specifically, if Figure 5 As shown, the grid nodes The right-pointing ray with vertex intersects the polygonal planning area at only one point (odd number), so it is located in the planning area, and the grid node The number of intersections between the right-pointing ray with vertex and the planning area polygon is 2 (an even number), so it is outside the planning area.

[0086] If there are restricted areas within the planned site, the above-mentioned "ray intersection method" can also be used to determine the relative position relationship between each grid node and the restricted area.

[0087] When the number of grid nodes located within the planning area and outside the restricted area is equal to When , it can be determined that the parameter scheme corresponding to the target individual meets the quantity constraint; if it is not equal to , then the parameter scheme corresponding to the target individual is determined to not meet the quantity constraint, and the annual power generation of the target individual is assigned a penalty value, such as 0.001 (preset minimum value).

[0088] S322: Determine whether the distance between adjacent grid points under the parameter scheme corresponding to the target individual is greater than the preset minimum distance. .

[0089] In this embodiment, the minimum value of the distance between adjacent grid nodes is determined , the calculation formula is:

[0090] ;

[0091] judge and If the minimum value of the spacing between adjacent grid points is greater than or equal to the preset minimum spacing, the parameter solution corresponding to the target individual is determined to meet the spacing constraint; if the minimum value of the spacing between adjacent grid points is less than the preset minimum spacing, the parameter solution corresponding to the target individual is determined to not meet the spacing constraint, and the annual power generation of the target individual is assigned a penalty value, such as 0.001.

[0092] S330. For the two-dimensional grid parameter scheme corresponding to each entity, determine the intersection point M between the outgoing submarine cable and the outer boundary of the planned area based on the positional relationship between the geometric center of gravity of the planned area and the onshore centralized control center; calculate the distance between each grid point of the two-dimensional grid within the planned area and the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station ( Figure 6 ).

[0093] In some embodiments, for the two-dimensional grid parameter scheme corresponding to each individual, each grid point of the two-dimensional grid in the planning area is used as an alternative location for the booster station, and the location of the booster station in the planning area is determined with the goal of minimizing the line between the booster station and each wind turbine in the planning area.

[0094] S340: For the individuals that meet the constraints in step S320, obtain the coordinates of each grid node in the planning area in the reference coordinate system to form a set WF_set. Then, combined with S330 to determine the construction site of the booster station, calculate the annual power generation of all wind turbines in the planning area under the corresponding parameter scheme ( Figure 7 ).

[0095] S341. Divide basic wind conditions based on wind speed and wind direction, and combine with a representative year wind resource data set to determine basic wind conditions corresponding to each period in the representative year, as well as the proportion of each basic wind condition in the representative year and the representative wind speed and representative wind direction of each basic wind condition.

[0096] S341a, based on the cut-in wind speed of the planned installation model in the planning area and cut-out wind speed As lower and upper limits, combined with the preset wind speed calculation interval , dividing the wind speed range into multiple different ranges.

[0097] By definition, the total , and the center value of the mth wind speed interval is .

[0098] S341b, according to the preset number of wind direction sectors , the 0-360° wind direction angle is evenly cut to obtain multiple different wind direction sectors.

[0099] By definition, the size of the wind direction sector is , let the center value of the first wind direction interval be 0, then the center value of the nth wind direction interval is .

[0100] S341c, by combining the wind direction sectors and wind speed intervals divided above, we can get multiple different basic wind conditions. According to the definition, the total number of basic wind conditions is .

[0101] For each basic wind condition, its representative wind speed and representative wind direction are respectively the center values ​​of the wind direction sector and wind speed interval that constitute the basic wind condition. Assuming that the rth basic wind condition consists of the mth wind speed interval and the nth wind direction sector, the representative wind speed and representative wind direction of the basic wind condition are and .

[0102] S341d. Process the representative annual wind resource dataset at the hub height of the corresponding wind turbine obtained in step S100, and classify the period into the corresponding basic wind condition according to the wind direction and wind speed of each period.

[0103] By counting the ratio of the number of time periods under each basic wind condition to the number of time periods in the wind resource dataset, we can obtain the proportion of each basic wind condition. The corresponding set can be expressed as ,in Refers to the proportion of the rth basic wind condition.

[0104] S342. Based on the representative wind speed and representative wind direction of each basic wind condition and in combination with the location of each wind turbine in the planned area, calculate the wind speed loss of each wind turbine in the area affected by the wake of the upwind wind turbine under each basic wind condition.

[0105] According to the basic wind conditions along the target The following represents the relative position before and after the wind direction. The grid nodes in WF_set are sorted from sequence number 1, and then the wind speed loss of the wind turbine to be installed at each grid node is quantified in sequence using the analytical model.

[0106] Assume the target grid node number is ,when When , the sequence number of the upwind grid node is , to calculate the sequence number Taking the wind speed loss and power generation of a wind turbine as an example, the detailed process is as follows:

[0107] when When , there is no other wind turbine upwind of the wind turbine at this grid node, so the wind speed loss is ;

[0108] when When , the wind turbine rotor disk at the target node is discretized, and the average value of the wind speed loss at each discrete point is calculated, thereby obtaining the wind speed loss of the wind turbine at the target grid node p:

[0109] ;

[0110] Where, is the total number of discrete points within the wind turbine rotor disk at node number p, Refers to the wind speed loss at the oth discrete point. In this embodiment, the square sum superposition method is used to deal with the overlapping effect of the wakes of multiple wind turbines in the upwind direction, which is calculated by the following formula: :

[0111] ;

[0112] Where, Indicates the serial number is The wind speed loss of the isolated wake of the wind turbine at the grid node at the oth discrete point within the wind turbine rotor disk at the node with sequence number p is calculated as follows:

[0113] ;

[0114] ;

[0115] ;

[0116] ;

[0117] ;

[0118] Where, 、 and The discrete point o and the serial number The flow direction, span direction and vertical spacing of the center point of the wind turbine rotor disk at the node, and Refers to the serial number respectively The thrust coefficient and wake expansion coefficient of the wind turbine at the grid node of the wind turbine are calculated based on existing research. With node The effective turbulence intensity of the wind turbine at are closely related and satisfy the following relationship:

[0119] ;

[0120] Where, and are adjustable parameters, and the recommended values ​​are 0.38 and 0.004 respectively. When q = 1, it means that there are no other wind turbines upwind of the wind turbine at node q, so the effective turbulence intensity is approximately equal to the turbulence intensity at the representative height, that is:

[0121] ;

[0122] when When , the effective turbulence intensity sensed by the wind turbine at this node includes not only the inflow turbulence intensity but also the additional turbulence intensity generated by the operation of the upstream wind turbine. The calculation formula is:

[0123] ;

[0124] ;

[0125] Where, and They represent the shielding area of ​​the wind turbine rotor at node q caused by the isolated wake of the wind turbine at node k, and the additional turbulence intensity at the wind turbine at node q. The calculation formula is:

[0126] ;

[0127] ;

[0128] Where, is the effective turbulence intensity of the wind turbine at node k, is the flow distance between the wind turbines at node k and node q along the representative wind direction.

[0129] In this embodiment, a "virtual wind turbine" is deployed at the booster station. Unlike the actual wind turbines to be installed within the planned site, the "virtual wind turbine" is always in a shutdown state. That is, regardless of changes in inflow wind conditions, its output power remains constant at zero, and its theoretical thrust coefficient is also zero, indicating that its presence does not obstruct the incoming wind farm. However, a thrust coefficient of zero can lead to overflow errors when evaluating the wind farm's wake effect using analytical models in subsequent steps. Therefore, in this embodiment, the thrust coefficient of the "virtual wind turbine" is set to 0.001 to ensure computational stability.

[0130] S343. Determine the effective wind speed of each wind turbine under each basic wind condition based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine.

[0131] Based on the wind speed loss calculated in step S342, combined with the target basic wind condition Representative wind speed , we can get the effective wind speed of the wind turbine at the grid node number p :

[0132] .

[0133] S344. Determine the power generation of each wind turbine under each basic wind condition based on the effective wind speed of each wind turbine under each basic wind condition, and then determine the power generation under each basic wind condition.

[0134] When the serial number When the grid node is the booster station represented by the "virtual wind turbine", take its thrust coefficient =0.001, power generation ; and when the serial number When a real wind turbine is inserted at the grid node, the effective wind speed obtained above is , combined with the wind speed-aerodynamic parameter list obtained in step S100, the thrust coefficient of the wind turbine can be obtained by referring to the following formula: and power generation :

[0135] ;

[0136] ;

[0137] Where, and The closest Two typical wind speeds, satisfying , ,as well as Corresponding to the list and thrust coefficient and power.

[0138] ;

[0139] Where, Refers to the rth basic wind condition power generation; Target base wind conditions The power generation of the wind turbine at the grid node numbered p in the next layout plan.

[0140] S345. Based on the power generation under each basic wind condition and the proportion of each basic wind condition in the representative year, determine the annual power generation of the planned site in the representative year.

[0141] ;

[0142] Where, To plan the annual power generation of the site; Refers to the rth basic wind condition respectively The proportion of wind power and the power generation under the basic wind conditions.

[0143] S400: Determine a two-dimensional grid based on optimal parameters of the two-dimensional grid, and then determine locations of planned installation of wind turbines and booster stations within the planned area based on grid points of the two-dimensional grid.

[0144] S410. Determine wind turbine rows based on each first straight line on the two-dimensional grid determined by the optimal parameters. The wind turbines (including virtual wind turbines) on the first straight line form a row. Determine the number of wind turbines located within the planned site on each wind turbine row (the booster station is regarded as a "virtual wind turbine", that is, the wind turbine count in its row is the number of real wind turbines + 1).

[0145] S420: Based on the number of wind turbines in each wind turbine row within the planned area, adjust the locations of wind turbines within the planned area according to different situations.

[0146] When the number of wind turbines on the wind turbine row is 1, the distance from the wind turbine position to the intersection of the first straight line and the planned site boundary is set as the second variable.

[0147] When the number of wind turbines on the wind turbine row is 2, place the two wind turbines at the two intersections of the corresponding first straight line and the planned site boundary. Figure 8 In the case of "Typical Row 1" in Figure 1, the two wind turbines only need to be adjusted to the two intersection points of the row line and the geometric boundary of the planned site (the blue squares and purple diamonds in the figure respectively indicate the wind turbines before and after adjustment). There are no design variables that need to be optimized.

[0148] When the number of wind turbines on a wind turbine row is greater than 2, the two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned area, and the spacing between adjacent wind turbines in the wind turbine row is used as the first variable. Figure 8 In the case of "Typical Row 3", after adjusting the wind turbines at both ends of the row to the intersection of the row and the planned site, it is necessary to further optimize the spacing between any two wind turbines in the row (the blue squares and orange diamonds in the figure represent the wind turbines before and after the adjustment, respectively). The set of corresponding design variables is ,in, It indicates the distance between the first and second wind turbines in the third row. The meanings of other variables are similar.

[0149] Taking the first and second variables as optimization variables and maximizing the annual power generation of the planned area as the goal, combined with the optimization constraints, a genetic algorithm is used to determine the optimal first and second variables, and based on the first and second variables, the position of each wind turbine on each wind turbine row in the planned area is determined.

[0150] In this embodiment, the optimization constraints include the following two: 1) the distance between any two wind turbines is greater than a preset minimum distance threshold; 2) when there is a restricted area within the planning site, each wind turbine must be outside the restricted area.

[0151] In this embodiment, a genetic algorithm is used to generate an initial population, wherein each individual in the population represents a set of values ​​of a first variable and a second variable set. In the corresponding layout plan, it is necessary to first determine whether the aforementioned two constraints are met. Furthermore, for individuals that meet the constraints, the annual power generation of the wind farm is calculated using the calculation method in steps S341-S345 (still assuming that the booster station is located at a "virtual wind turbine"). For those that do not meet the constraints, their power generation is taken as a minimum value, such as 0.001.

[0152] Example 2: This example is a device for optimizing the layout of offshore wind farms taking into account booster stations, including:

[0153] The information acquisition module is used to obtain the boundary information of the planned site, the number and model parameters of the wind turbines to be installed in the site, and the representative annual wind resource dataset at the hub height of the wind turbines;

[0154] A grid generation module, configured to generate a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines;

[0155] The parameter optimization module is used to determine the optimal parameters of the two-dimensional grid using genetic algorithms, with the parameters of the two-dimensional grid as variables and the grid points of the two-dimensional grid within the planning area as the locations for installing wind turbines and booster stations, with the goal of maximizing the annual power generation of the planning area;

[0156] The point determination module is used to determine the two-dimensional grid based on the optimal parameters of the two-dimensional grid, determine the wind turbine row based on the first straight line on the two-dimensional grid, place the two wind turbines at the two intersections of the corresponding first straight line and the boundary of the planned site, and use the spacing between adjacent wind turbines in the wind turbine row as the first variable. With the goal of maximizing the annual power generation of the planned site, a genetic algorithm is used to determine the optimal first variable.

[0157] Example 3: This example is a storage medium on which a computer program that can be executed by a processor is stored. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station described in Example 1 are implemented.

[0158] Example 4: This example is an offshore wind farm layout optimization design device having a memory and a processor. The memory stores a computer program that can be executed by the processor. When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station described in Example 1 are implemented.

[0159] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the above-mentioned functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More specifically, given the properties, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the routine skills of an engineer. Therefore, a person skilled in the art can implement the present invention set forth in the claims using ordinary skills without undue experimentation. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0160] If the above functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the above methods in various embodiments of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0161] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0162] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable media on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other media, and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0163] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0164] In the above description of this specification, reference to the terms "one embodiment / example," "another embodiment / example," or "certain embodiments / examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0165] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

[0166] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for optimizing the layout of offshore wind farms considering booster stations, characterized in that: include: Obtain the boundary information of the planned site, the number and model parameters of the wind turbines to be installed in the site, and a representative annual wind resource dataset at the hub height of the wind turbines; generating a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines; The genetic algorithm is used to determine the optimal parameters of the two-dimensional grid, with the parameters of the two-dimensional grid as variables, the grid points of the two-dimensional grid in the planning area as the locations where wind turbines and booster stations are to be installed, and the goal is to maximize the annual power generation of the planning area. Based on the optimal parameters of the two-dimensional grid, the two-dimensional grid is determined, and the wind turbine row is determined based on the first straight line on the two-dimensional grid. The two wind turbines at the ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site. The spacing between adjacent wind turbines in the wind turbine row is used as the first variable. With the goal of maximizing the annual power generation of the planned site, a genetic algorithm is used to determine the optimal first variable. The grid points of the two-dimensional grid within the planned site are used as the locations for installing wind turbines and booster stations, including: Based on the geometric center of gravity of the planned site and the positional relationship between the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned site; Calculate the distance from each grid point of the two-dimensional grid within the planning area to the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station; The parameters of the two-dimensional grid include D r ,D c ,α,β, the distance between adjacent first straight lines is D r ; The distance between adjacent second straight lines is D c The angle between the first straight line and the preset first direction is α; the angle between the second straight line and the first straight line is β; The calculation of the annual power generation of the planned site includes: Determine whether the number of grid points in the two-dimensional grid within the planning area is equal to N wt +1, where N wt The number of wind turbines to be installed in the planned area; If the number of grid points in the planning area is not equal to N wt +1, the preset minimum value is used as the annual power generation of the planned site; otherwise, it is determined whether the distance between adjacent grid points is greater than the preset minimum distance; If the spacing between adjacent grid points is less than the preset minimum spacing, the preset minimum value is used as the annual power generation of the planned site. Otherwise, the annual power generation of the planned site is calculated based on the location of each wind turbine in the planned site, combined with the model parameters and the representative annual wind resource data set. The calculation of the annual power generation of the planned area based on the location of each wind turbine in the planned area, combined with the model parameters and the representative annual wind resource data set, includes: Assume that the boost station is located at a virtual wind turbine, the output power of the virtual wind turbine is always 0, and the thrust coefficient is set to 0.001; Divide the basic wind conditions based on wind speed and wind direction, and combine with the representative annual wind resource dataset to determine the basic wind conditions corresponding to each period of the representative year, as well as the proportion of each basic wind condition in the representative year and the representative wind speed and representative wind direction of each basic wind condition; Based on the representative wind speed and representative wind direction of each basic wind condition and the location of each wind turbine in the planned area, calculate the wind speed loss of each wind turbine in the area affected by the wake of the upwind wind turbine under each basic wind condition; Determine the effective wind speed of each wind turbine under each basic wind condition based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine; Based on the effective wind speed of each wind turbine under each basic wind condition, the power generation of each wind turbine under each basic wind condition is determined, and then the power generation under each basic wind condition is determined; Based on the power generation under each basic wind condition and the proportion of each basic wind condition in the representative year, the annual power generation of the planned site in the representative year is determined.

2. The offshore wind farm layout optimization design method considering booster stations according to claim 1 is characterized in that: include: When the number of wind turbines on the wind turbine row is 1, the distance between the wind turbine point and the intersection of the first straight line and the planned site boundary is set as the second variable; When the number of wind turbines on the wind turbine row is 2, place the two wind turbines at the two intersections of the corresponding first straight line and the boundary of the planned site; When the number of wind turbines in a wind turbine row is greater than 2, the two wind turbines at both ends of the wind turbine row are placed at the two intersections of the corresponding first straight line and the boundary of the planned site, and the spacing between adjacent wind turbines in the wind turbine row is used as the first variable; Taking the first and second variables as optimization variables and maximizing the annual power generation of the planned site as the goal, a genetic algorithm is used to determine the optimal first and second variables.

3. The offshore wind farm layout optimization design method considering booster stations according to claim 1 is characterized in that: The basic wind conditions based on wind speed and wind direction include: The cut-in wind speed V of the wind turbine model to be installed in the planning area cut_in and cut-out wind speed V cut_out As the maximum value and the minimum value, multiple wind speed intervals are divided between the maximum value and the minimum value; Evenly divide the wind direction angle from 0-360° into multiple wind direction sectors; The wind speed ranges and wind direction sectors are combined in pairs to form multiple basic wind conditions.

4. A device for optimizing the layout of offshore wind farms considering booster stations, characterized in that: include: The information acquisition module is used to obtain the boundary information of the planned site, the number and model parameters of the wind turbines to be installed in the site, and the representative annual wind resource dataset at the hub height of the wind turbines; A grid generation module, configured to generate a two-dimensional grid covering the planned area, the two-dimensional grid being formed by the intersection of a plurality of mutually parallel first straight lines and a plurality of mutually parallel second straight lines; The parameter optimization module is used to determine the optimal parameters of the two-dimensional grid using genetic algorithms, with the parameters of the two-dimensional grid as variables and the grid points of the two-dimensional grid within the planning area as the locations for installing wind turbines and booster stations, with the goal of maximizing the annual power generation of the planning area; a point determination module for determining a two-dimensional grid based on optimal parameters of the two-dimensional grid, determining a wind turbine row based on a first straight line on the two-dimensional grid, placing two wind turbines at both ends of the wind turbine row at the intersections of the corresponding first straight line and the boundary of the planned site, and using the spacing between adjacent wind turbines in the wind turbine row as a first variable, with the goal of maximizing the annual power generation of the planned site, using a genetic algorithm to determine the optimal first variable; The grid points of the two-dimensional grid within the planned site are used as the locations for installing wind turbines and booster stations, including: Based on the geometric center of gravity of the planned site and the positional relationship between the onshore centralized control center, determine the intersection point M of the outgoing submarine cable and the outer boundary of the planned site; Calculate the distance from each grid point of the two-dimensional grid within the planning area to the line between the geometric center of gravity and the intersection point M, and select the grid point with the shortest distance as the location of the booster station; The parameters of the two-dimensional grid include D r ,D c ,α,β, the distance between adjacent first straight lines is D r ; The distance between adjacent second straight lines is D c The angle between the first straight line and the preset first direction (in this example, the positive direction of the X-axis of the reference coordinate system) is α; the angle between the second straight line and the first straight line is β; The calculation of the annual power generation of the planned site includes: Determine whether the number of grid points in the two-dimensional grid within the planning area is equal to N wt +1, where N wt The number of wind turbines to be installed in the planned area; If the number of grid points in the planning area is not equal to N wt +1, the preset minimum value is used as the annual power generation of the planned site; otherwise, it is determined whether the distance between adjacent grid points is greater than the preset minimum distance; If the spacing between adjacent grid points is less than the preset minimum spacing, the preset minimum value is used as the annual power generation of the planned site. Otherwise, the annual power generation of the planned site is calculated based on the location of each wind turbine in the planned site, combined with the model parameters and the representative annual wind resource data set. The calculation of the annual power generation of the planned area based on the location of each wind turbine in the planned area, combined with the model parameters and the representative annual wind resource data set, includes: Assume that the boost station is located at a virtual wind turbine, the output power of the virtual wind turbine is always 0, and the thrust coefficient is set to 0.001; Divide the basic wind conditions based on wind speed and wind direction, and combine with the representative annual wind resource dataset to determine the basic wind conditions corresponding to each period of the representative year, as well as the proportion of each basic wind condition in the representative year and the representative wind speed and representative wind direction of each basic wind condition; Based on the representative wind speed and representative wind direction of each basic wind condition and the location of each wind turbine in the planned area, calculate the wind speed loss of each wind turbine in the area affected by the wake of the upwind wind turbine under each basic wind condition; Determine the effective wind speed of each wind turbine under each basic wind condition based on the representative wind speed under each basic wind condition and the wind speed loss of each wind turbine affected by the wake of the upwind wind turbine; Based on the effective wind speed of each wind turbine under each basic wind condition, the power generation of each wind turbine under each basic wind condition is determined, and then the power generation under each basic wind condition is determined; Based on the power generation under each basic wind condition and the proportion of each basic wind condition in the representative year, the annual power generation of the planned site in the representative year is determined.

5. A storage medium having stored thereon a computer program executable by a processor, characterized in that: When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station as described in any one of claims 1 to 3 are implemented.

6. An offshore wind farm layout optimization design device, comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that: When the computer program is executed, the steps of the offshore wind farm layout optimization design method considering the booster station as described in any one of claims 1 to 3 are implemented.

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